Fund Performance Expectations, Recommendations and Results Paper

Fund performance – Initial Expectations, Future Recommendations, Final Performance, Reporting on Delegation

Introduction

The fundamental strategic objective of our fund was to reduce risk through a diversified portfolio. From this we analysed a variety of investment strategies and techniques to discover the most appropriate approach to match our risk appetite. From the evidence presented below we concluded that this could be achieved by creating a fund replicating the FTSE 100, usually referred to as an index fund. We found that active investment techniques had unclear benefits, and any abnormal profits made were offset by high transaction costs. In another effort to reduce transaction costs we preferred to invest only in the UK to avoid exchange rate spreads, whilst still gaining the benefits of the FTSE 100’s global exposure for our diversification needs. Although we found that several security analysis techniques have some merit, the evidence provided was not convincing enough to base an investment strategy on.

As a group we expected our fund to achieve a return that matched the market performance before transaction costs and tracking error were taken into consideration. The results show that this was a reasonable expectation, as our fund did in fact mimic the returns of the FTSE100. We calculated our investment in each company based on the index method detailed below. We then delegated each member to invest in 25 predetermined companies.

Active vs. Passive Investment

In the active vs. passive debate it is important to examine both the performance of active managers as well as the impact that transaction costs have on returns. If managers cannot beat the market after fees or the returns are too low to justify trying to replicate manager techniques, then it is sensible to pursue a strategy of passive investment. The benefit of passive investing is the low transaction costs incurred due to the low turnover of shares. Pursuing a strategy of holding the market portfolio (index fund) is a possible way of tracking the overall market performance (e.g. FTSE100) and this strategy minimises transaction costs. The downside of this strategy is that by its very nature, the fund cannot beat the market, however it can track it very closely, save for some tracking error. Even if we were to conclude that it is possible for active fund managers to achieve abnormal returns after fees, we must place ourselves in the context of our current situation in order to choose the appropriate strategy. In order to properly analyse shares, financial institutions and funds have dedicated equity research teams that have specialist knowledge of specific industries, or in some cases knowledge of just a handful of companies. So by the nature of the stock market, we would be competing against these sophisticated investors who are analysing companies and the market as a full time occupation. It would be hard to argue that any investing techniques we have learned at undergraduate level or any special insight we think we have into a share would actually hold any weight in the real world of the markets. After all, even if we did try to pursue an active investment strategy, it is likely that most of our returns would be wiped out by the high transaction costs we would incur. Therefore after taking all of these factors into consideration, and the evidence we present below, our group decided that a passive investment approach would be the most appropriate.

The transaction costs involved in seeking abnormal returns through active management have a large impact on the overall fund performance. From Wermers (2000) we can see that even though funds may outperform the market in terms of stock returns, most of these returns are not realised as they are largely lost to transaction costs. French (2008) also investigated the cost that investors pay when trying to beat the market through active management. He finds evidence to show that the costs to investors by pursuing active management is significant on a yearly basis and questions the wisdom of why active investors choose to play such a losing game. The paper points out that although some investors may achieve abnormal returns, the whole business of active management is a negative sum game due to the costs and fees involved. The appetite for actively managed funds may still persist due to the promotion and recognition that star performers get in the media. We should be cautious however and consider that winners tend to be loud and losers tend to be quiet. Over a long period, these stars tend to fade and there is evidence that shows that fund managers tend to under-perform alternative passive strategies. The fact that some managers do consistently outperform the market over a long period of time does not automatically confirm that given the right strategy, abnormal returns can be achieved. Rather we must consider the luck vs. skill debate and thus whether these star performers are mainly explained through probability. The skilled manager debate has continued ever since Jensen (1968) who concluded that on average mutual funds couldn’t beat the market and that there was little evidence that outperforming the market was anything more than chance. The issue has further been studied by Barras, et al (2010) who found that 75% of funds do not generate returns in excess of the risk taken on. The study finds that after adjusting for luck, their sample exhibits no skilled managers (those with positive alphas) in the long run in recent years, but a relatively large proportion, 23.5%, of unskilled managers who consistently under-perform over a long period. Almost identical results are found by Cuthbertson et al (2010) who go on to suggest that non-sophisticated investors should pursue a strategy of buying low cost index funds. Busse et al (2010) also find similarly that there is a lack of evidence that skill can describe positive alphas and that in general there isn’t much indication of superior performance in actively managed funds. Further evidence can be seen in Ackermann et al (1999) again highlights that after fees and costs, hedge funds are unable to beat the market consistently.

This evidence shows that on average fund managers tend not to outperform the market when pursuing active investing strategies. Therefore if professionals cannot even consistently achieve abnormal returns, it would be unwise to expect that our group could. We concluded that we would pursue a passive strategy as we believed it was the most appropriate given the evidence.

Diversification

Another issue to consider when creating an investment portfolio is the level of diversification required. This includes deciding how many companies to invest in, whether to invest purely domestically or internationally as well as what sectors and size of companies should be included. These choices are important because diversification brings unique advantages to a portfolio. Brealey et al (2008) explain that diversification allows an investor to remove the element of unsystematic risk that each stock carries, leaving only systematic risk. Given that our investment strategy has a risk averse behaviour it is clear that diversification is an important factor in reducing the portfolio's risk.
A key element of the diversification procedure is in deciding how many companies to invest in. Evans and Archer (1968) discuss the relationship between the number of securities held in a portfolio and the diversification benefits that are garnered. They posit that the investor must analyse the marginal returns of holding each new individual security and by how much they reduce the variation of the portfolio in order to see if the additional cost can be justified. This will reveal whether the stocks correlation to the portfolio provides any further reduction in unsystematic risk. After investigating this they find evidence that there is little justification in having portfolios that hold more than 10 securities. This is around half of the 20 securities commonly quoted in finance textbooks (Brealey et al, 2008).

However more recent research by Tang (2004) suggests that both figures may be too low. He finds that 95% of diversifiable risk can be removed by holding 20 securities, but holding 100 will remove 99% of the risk. Whilst it would be helpful to perform a marginal analysis when choosing the securities for our portfolio, it was not possible given the lack of resources. Therefore it was prudent to follow the literature and invest in 100 companies so that we reduced unsystematic risk by as much as possible.

Another factor that must be considered is whether to diversify internationally. Solnik (1974) details the advantages of investing not only domestically but also in foreign securities. He explains that there is little correlation between different countries' exchanges, so if one countries' securities are performing poorly then this is likely to counterbalanced by the strong performance of another countries' securities', thus the portfolio's losses would be minimized. However, globalisation has created a much smaller world, with businesses and markets ever more connected their differences cannot be relied upon with such certainty any more. The events of the past four years have illustrated how heavy losses can be sustained on many of the major stock markets simultaneously.

Indeed, Butler and Joaquin (2002) found that during a stock market downturn the correlation between countries' securities increased, thus reducing the benefit of holding an internationally diversified portfolio. This suggests that the advantages of foreign trading are somewhat unclear. For this reason our investment strategy did not include securities from France or Australia due to the extra costs (currency commissions and spreads) and resources (investigations into what companies to include) needed for a benefit which may not have materialised.

This decision was also taken in the knowledge investing in the FTSE 100 would still provide an element of international diversification. Errunza et al (1999) found that the benefits of foreign trading can be gained by investing domestically. They were able to create home-made diversification by investing in multinational companies and other organisations that held claims on foreign assets. Given that 70% of FTSE 100 earnings originate outside of the UK , our strategy still gains whatever international diversification benefits are available.

Finally, diversification also depends on what sectors and firm sizes to invest in. Selecting 100 companies provides greater scope to include more sectors and indeed the FTSE 100 does offer enough sectors to diversify. It does not, however, include any small companies, which would be an additional source of diversification. Given that a major part of our investment strategy is to minimise costs, the diversification benefits are outweighed by the additional costs from commissions and spreads on small firms.

Index Funds

We have chosen an index-tracker approach as our investment strategy. This was chosen based on evidence found in financial theory and our preference to be risk averse. The FTSE 100 was chosen as the index to be followed because of the lower commission fees and smaller spreads involved in trading these shares, as well as evidence found that larger companies are less risky than small companies. In the creation of an index fund there are three different approaches that can be taken – full replication, stratification and sampling (Meade and Salkin, 1989). We opted for the full replication method. This involved holding all of the shares in the FTSE 100 in the same proportion as the index, which means the allocations of funds to each share were calculated to match there weighted capitalization in the index. The full replication method has the major advantage over the other methods in that it closely tracks the market performance and eliminates firm-specific risk if the portfolio holding exactly equals the index holding. We also knew there would be no adjustment costs for additions and deletions to the FTSE 100 throughout the duration of having our portfolio as these only happen quarterly. However, the full replication method has high set-up and divestment costs and these obviously increase with the number of companies in the portfolio. As was found, these transaction costs can reduce portfolio performance and eliminate the market return.

The stratification and sampling methods are aimed at reducing the number of companies required in a portfolio while also still closely tracking the index. Therefore these methods try to gain the benefits of a fully replicated index fund but with significantly less transactions costs. There are a number of disadvantages, however, as they require a lot of managerial judgement and if badly implemented can cause large tracking errors (Meade and Salkin, 1989). Therefore, it can be said these methods are less likely to achieve market performance because the discrepancy between portfolio performance and market performance increases. They also create less diversified portfolios and thus firm-specific risk is increased. It was for these reasons we chose the full replication method instead of stratification or sampling as our stated objective was to match the market return as closely as possible.

Two limitations were found when implementing our chosen approach. Due to the difference in share price at the time of calculating the quantity of shares to buy and the share price when executing the trade we were unable to exactly match the weighted capitalization of our portfolio and that of the index. Also our portfolio had six companies missing as the FTSE 100 on Finesse only has 96 companies when it actually has 102 in real life according to the LSE website.

Security Analysis Techniques Considered

Momentum Strategy

Amongst the numerous analysts and portfolio managers there is a widely held opinion that momentum strategies can produce significant profits. Jegadeesh and Titman (1993) (also referred to as JT from this point onwards) have documented a variety of momentum strategies that buy stocks with high returns over the previous 3 to 12 months and sell those with poor returns over the same period, earning profits of about 1% per month. While these results have been widely accepted, the source of the profits and the interpretation of the evidence is debated. Some believe that these results are strong evidence of "market inefficiency," whilst others argue that the returns from this method of strategic investment is either compensation for risk, or possibly, the product of data mining.

Over the 1990 to 1997 sample period, the data had shown that strategies provided by JT regarding their momentum theories of strategic investment continued to be profitable and the past winners outperform past losers by approximately the same extent as in the earlier period.

This evidence would suggest that the anomalies of the momentum portfolio in the 13 to 60 months following the formation month is negative consistent with the views that support the behavioural models. The behavioural models argue that momentum profits are generated by delayed overreaction. Jagadeesh and Titman believe, however, that this evidence should be viewed with some caution as there is no evidence of a return reversal until 4 years after the formation date. JT only noticed a partial and marginal return reversal in the later time period. Yet, the momentum profits in the two time periods are essentially equal.

Contrarian Strategy

Another view held by managers and analysts alike is the contrarian theory provided by DeBondt and Thaler (1985, 1987), suggesting that by buying past losers and selling winners, investors can achieve abnormal returns.

Trading strategies that buy past winners and sell past losers realise significant abnormal returns over the 1965-1989 period. Their study showed that over a 3-5 year holding period, stocks that performed poorly over the previous 3 -5 years managed to achieve higher returns than the stocks that performed well over the same period. Another study by the duo in 1993, selected stocks based on their past 6-month returns and held them for 6 months, realising an excess return of 12.01% per year on average. Additional evidence indicates that the profitability relative to strength strategies are not due to their systematic risk. The results of the test also indicate that the relative strength profits cannot be attributed to lead-lag effects that result from delayed stock price reactions to common factors. The 1992 study by Jagadeesh and Titman found that the delayed stock price reactions resulting in a lead-lag structure accounted for less than 5% of contrarian profits with the majority of the profits being as a result of a reversal of firm-specific stock returns. The evidence is, however, consistent with delayed price reactions to firm-specific information.

Regarding DeBondt and Thaler’s findings, some argue that the results can be explained by the systematic risk of their contrarian portfolios and the size effect. In addition, since the long-term losers outperform the long-term winners only in the January months of the study, it is unclear whether their results can be attributed to an overreaction. This occurs when investors who buy past winners and sell past losers move the process away from their long-run values temporarily and thereby cause prices to overreact. This interpretation is consistent with the analysis of DeLong, Shleifer, et al (1990) who investigated the implications of what they call “positive feedback traders” on market price. Alternatively, it is possible that the market under-reacts to the information about the short-term prospects of firms and over-reacts to the information about their long-term prospects. This is conceivable given that the nature of information available about firm’s short-term prospects, such as earnings forecasts, is different from the nature of the more uncertain information that is used by investors to assess a firm’s longer-term prospects.

While the momentum and contrarian theories have some practical merit, it would have been unfeasible for our group to attempt to implement them in our investment strategy due to the time constraints. Profits normally occurred within a three to six month time period, while our group only had approximately seven weeks to use these techniques in an attempt to beat the market. The data which was also required was beyond our resource capabilities as significant time and information would have been required to find past winner and loser stocks. It must also be noted that there are several other possible explanations for these phenomena and to place all our trust in such findings would be unwise.

Fund Performance

Initial Fund Value £ 100,000,000

Share Price Profit £ 80,265
Dividends Received £ 617,596
Share Commission £ -789,443
Total Profit/Loss of Share Portfolio £ -91,582

Money Market Interest £ 31,759

Total Value of Fund After Divestment £ 99,940,177

Overall we lost £ -59,823 which was largely a result of the share commission costs paid on investment and divestment. This was predicted in our initial expectations; however our strategy was designed for long term investment which would be able to absorb these costs more effectively than a seven week investment period. In the real market our fund would only see such a heavy divestment at the point of liquidation. Therefore this divestment had an unrealistic impact on our fund’s performance, reducing our return to -0.6% compared to the FTSE100’s 0.5%. In the longer term more dividends would also be collected which would cover the share commission costs incurred.

If this had been a longer term project we would suggest the following recommendations: Firstly ever quarter the fund would be readjusted to incorporate the changes in FTSE100 constituents in order to be able to mimic the market. Further the income we received from dividends and interest would be reinvested annually [or quarterly at every readjustment date?] (to reduce transaction costs) so as to minimise the amount of cash lying idle. When executing our strategy we found that finesse would not let us buy shares in a small number of shares [how many exactly?] and this lead us to having some cash in the bank that should have otherwise been invested in the market. In future we would hope to resolve this issue in order to fully replicate the market by owning shares in each of the FTSE100 listed companies.

Conclusion

Our initial aim was to reduce risk by diversifying our portfolio between the largest 100 companies in the UK. We sought to reduce transaction costs by investing in the FTSE 100 which has the lowest commissions and spreads, while also offering us some international exposure due to the nature of the operations of the majority of FTSE100 companies. In our research we found that transaction costs are a significant reason for active funds performing worse on average than alternate passive strategies. Our strategy was affected by large divestment costs that would not otherwise have been incurred as this is a long term strategy. Overall we believe we have successfully achieved our initial objectives and our fund performance matched our expectations.

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